Digital signal processing (DSP) Books

Book SynopsisProvides a comprehensive resource on what has become the dominant paradigm in designing novel interaction methods, involving gestures, speech, text, touch and brain-controlled interaction, embedded in innovative and emerging human-computer interfaces.

Read more less

Book SynopsisProvides a comprehensive resource on what has become the dominant paradigm in designing novel interaction methods, involving gestures, speech, text, touch and brain-controlled interaction, embedded in innovative and emerging human-computer interfaces.

Read more less

Book SynopsisWith signal processing, we want to identify/characterize various physical processes, such as standard engineering variables (e.g. faults on bearings, dynamic properties of structures), as well as biology phenomena (e.g. genome sequencing), astronomy (e.g. measuring a black hole), social sciences (e.g. the spread of the corona virus) and the like. This book edition covers different topics from signal and information processing, including methods for signal processing, signal processing in medicine, image and video signal processing, and signal processing in engineering.Table of Contents Section 1 Methods for Signal Processing Chapter 1 Comparative Study and Analysis of Performances among RNS, DBNS, TBNS and MNS for DSP Applications Chapter 2 The Fourier Notation of the Geomagnetic Signals Informative Parameters Chapter 3 A Time Dependent Model for Image DenoisingSection 2 Methods for Signal Processing Chapter 4 An Efficient Signal Processing Algorithm for Detecting Abnormalities in EEG Signal Using CNN Chapter 5 Contribution to S-EMG Signal Compression in 1D by the Combination of the Modified Discrete Wavelet Packet Transform (MDWPT) and the Discrete Cosine Transform (DCT) Chapter 6 Improved Guided Image Fusion for Magnetic Resonance and Computed Tomography Imaging Chapter 7 A Biologically Inspired Algorithm for Low Energy Clustering Problem in Body Area NetworkSection 3 Image and Video Signal Processing Chapter 8 Segmentation of Visual Images by Sequential Extracting Homogeneous Texture Areas Chapter 9 Deep Learning in Visual Computing and Signal Processing Chapter 10 Pre-Processing Images of Public Signage for OCR Conversion Chapter 11 A Local Binary Pattern-Based Method for Color and Multicomponent Texture AnalysisSection 4 Engineering Applications of Signal Processing Chapter 12 An Adaptive EMD Technique for Induction Motor Fault Detection Chapter 13 Nondestructive Testing for Corrosion Evaluation of Metal Under Coating Chapter 14 Environment Perception Technologies for Power Transmission Line Inspection Robots Chapter 15 Feature Extraction Techniques of Non-Stationary Signals for Fault Diagnosis in Machinery Systems

Read more less

Book SynopsisThe parameter estimation and hypothesis testing are the basic tools in statistical inference. These techniques occur in many applications of data processing., and methods of Monte Carlo have become an essential tool to assess performance. For pedagogical purposes the book includes several computational problems and exercices. To prevent students from getting stuck on exercises, detailed corrections are provided.Table of ContentsPreface ix Notations and Abbreviations xi A Few Functions of Python® xiii Chapter 1 Useful Maths 1 1.1. Basic concepts on probability 1 1.2. Conditional expectation 10 1.3. Projection theorem 11 1.3.1. Conditional expectation 14 1.4. Gaussianity 14 1.4.1. Gaussian random variable 14 1.4.2. Gaussian random vectors 15 1.4.3. Gaussian conditional distribution 16 1.5. Random variable transformation 18 1.5.1. General expression 18 1.5.2. Law of the sum of two random variables 19 1.5.3. δ-method 20 1.6. Fundamental theorems of statistics 22 1.7. A few probability distributions 24 Chapter 2 Statistical Inferences 29 2.1. First step: visualizing data 29 2.1.1. Scatter plot 29 2.1.2. Histogram/boxplot 30 2.1.3. Q-Q plot 32 2.2. Reduction of dataset dimensionality 34 2.2.1. PCA 34 2.2.2. LDA 36 2.3. Some vocabulary 40 2.3.1. Statistical inference 40 2.4. Statistical model 41 2.4.1. Notation 42 2.5. Hypothesis testing 43 2.5.1. Simple hypotheses 45 2.5.2. Generalized likelihood ratio test (GLRT) 50 2.5.3. χ 2 goodness-of-fit test 57 2.6. Statistical estimation 58 2.6.1. General principles 58 2.6.2. Least squares method 62 2.6.3. Least squares method for the linear model 64 2.6.4. Method of moments 81 2.6.5. Maximum likelihood approach 84 2.6.6. Logistic regression 100 2.6.7. Non-parametric estimation of probability distribution 103 2.6.8. Bootstrap and others 107 Chapter 3 Inferences on HMM 113 3.1. Hidden Markov models (HMM) 113 3.2. Inferences on HMM 116 3.3. Filtering: general case 117 3.4. Gaussian linear case: Kalman algorithm 118 3.4.1. Kalman filter 118 3.4.2. RTS smoother 127 3.5. Discrete finite Markov case 129 3.5.1. Forward-backward formulas 130 3.5.2. Smoothing formula at one instant 133 3.5.3. Smoothing formula at two successive instants 134 3.5.4. HMM learning using the EM algorithm 135 3.5.5. The Viterbi algorithm 137 Chapter 4 Monte-Carlo Methods 141 4.1. Fundamental theorems 141 4.2. Stating the problem 141 4.3. Generating random variables 144 4.3.1. The cumulative function inversion method 144 4.3.2. The variable transformation method 147 4.3.3. Acceptance-rejection method 149 4.3.4. Sequential methods 151 4.4. Variance reduction 156 4.4.1. Importance sampling 156 4.4.2. Stratification 160 4.4.3. Antithetic variates 164 Chapter 5 Hints and Solutions 167 5.1. Useful maths 167 5.2. Statistical inferences 170 5.3. Inferences on HMM 226 5.4. Monte-Carlo methods 251 Bibliography 261 Index 263

Read more less

Book SynopsisNowadays, tensors play a central role for the representation, mining, analysis, and fusion of multidimensional, multimodal, and heterogeneous big data in numerous fields. This set on Matrices and Tensors in Signal Processing aims at giving a self-contained and comprehensive presentation of various concepts and methods, starting from fundamental algebraic structures to advanced tensor-based applications, including recently developed tensor models and efficient algorithms for dimensionality reduction and parameter estimation. Although its title suggests an orientation towards signal processing, the results presented in this set will also be of use to readers interested in other disciplines. This first book provides an introduction to matrices and tensors of higher-order based on the structures of vector space and tensor space. Some standard algebraic structures are first described, with a focus on the hilbertian approach for signal representation, and function approximation based on Fourier series and orthogonal polynomial series. Matrices and hypermatrices associated with linear, bilinear and multilinear maps are more particularly studied. Some basic results are presented for block matrices. The notions of decomposition, rank, eigenvalue, singular value, and unfolding of a tensor are introduced, by emphasizing similarities and differences between matrices and tensors of higher-order.Table of ContentsPreface xi Chapter 1. Historical Elements of Matrices and Tensors 1 Chapter 2. Algebraic Structures 9 2.1. A few historical elements 9 2.2. Chapter summary 11 2.3. Sets 12 2.3.1. Definitions 12 2.3.2. Sets of numbers 13 2.3.3. Cartesian product of sets 13 2.3.4. Set operations 14 2.3.5. De Morgan’s laws 15 2.3.6. Characteristic functions 15 2.3.7. Partitions 16 2.3.8. σ-algebras or σ-fields 16 2.3.9. Equivalence relations 16 2.3.10. Order relations 17 2.4. Maps and composition of maps 17 2.4.1. Definitions 17 2.4.2. Properties 18 2.4.3. Composition of maps 18 2.5. Algebraic structures 18 2.5.1. Laws of composition 18 2.5.2. Definition of algebraic structures 22 2.5.3. Substructures 24 2.5.4. Quotient structures 24 2.5.5. Groups 24 2.5.6. Rings 27 2.5.7. Fields 32 2.5.8. Modules 33 2.5.9. Vector spaces 33 2.5.10. Vector spaces of linear maps 38 2.5.11. Vector spaces of multilinear maps 39 2.5.12. Vector subspaces 41 2.5.13. Bases 43 2.5.14. Sum and direct sum of subspaces 45 2.5.15. Quotient vector spaces 47 2.5.16. Algebras 47 2.6. Morphisms 49 2.6.1. Group morphisms 49 2.6.2. Ring morphisms 51 2.6.3. Morphisms of vector spaces or linear maps 51 2.6.4. Algebra morphisms 56 Chapter 3. Banach and Hilbert Spaces – Fourier Series and Orthogonal Polynomials 57 3.1. Introduction and chapter summary 57 3.2. Metric spaces 59 3.2.1. Definition of distance 60 3.2.2. Definition of topology 60 3.2.3. Examples of distances 61 3.2.4. Inequalities and equivalent distances 62 3.2.5. Distance and convergence of sequences 62 3.2.6. Distance and local continuity of a function 62 3.2.7. Isometries and Lipschitzian maps 63 3.3. Normed vector spaces 63 3.3.1. Definition of norm and triangle inequalities 63 3.3.2. Examples of norms 64 3.3.3. Equivalent norms 68 3.3.4. Distance associated with a norm 69 3.4. Pre-Hilbert spaces 69 3.4.1. Real pre-Hilbert spaces 70 3.4.2. Complex pre-Hilbert spaces 70 3.4.3. Norm induced from an inner product 72 3.4.4. Distance associated with an inner product 75 3.4.5. Weighted inner products 76 3.5. Orthogonality and orthonormal bases 76 3.5.1. Orthogonal/perpendicular vectors and Pythagorean theorem 76 3.5.2. Orthogonal subspaces and orthogonal complement 77 3.5.3. Orthonormal bases 79 3.5.4. Orthogonal/unitary endomorphisms and isometries 79 3.6. Gram–Schmidt orthonormalization process 80 3.6.1. Orthogonal projection onto a subspace 80 3.6.2. Orthogonal projection and Fourier expansion 80 3.6.3. Bessel’s inequality and Parseval’s equality 82 3.6.4. Gram–Schmidt orthonormalization process 83 3.6.5. QR decomposition 85 3.6.6. Application to the orthonormalization of a set of functions 86 3.7. Banach and Hilbert spaces 88 3.7.1. Complete metric spaces 88 3.7.2. Adherence, density and separability 90 3.7.3. Banach and Hilbert spaces 91 3.7.4. Hilbert bases 93 3.8. Fourier series expansions 97 3.8.1. Fourier series, Parseval’s equality and Bessel’s inequality 97 3.8.2. Case of 2π-periodic functions from R to C 97 3.8.3. T-periodic functions from R to C 102 3.8.4. Partial Fourier sums and Bessel’s inequality 102 3.8.5. Convergence of Fourier series 103 3.8.6. Examples of Fourier series 108 3.9. Expansions over bases of orthogonal polynomials 117 Chapter 4. Matrix Algebra 123 4.1. Chapter summary 123 4.2. Matrix vector spaces 124 4.2.1. Notations and definitions 124 4.2.2. Partitioned matrices 125 4.2.3. Matrix vector spaces 126 4.3. Some special matrices 127 4.4. Transposition and conjugate transposition 128 4.5. Vectorization 130 4.6. Vector inner product, norm and orthogonality 130 4.6.1. Inner product 130 4.6.2. Euclidean/Hermitian norm 131 4.6.3. Orthogonality 131 4.7. Matrix multiplication 132 4.7.1. Definition and properties 132 4.7.2. Powers of a matrix 134 4.8. Matrix trace, inner product and Frobenius norm 137 4.8.1. Definition and properties of the trace 137 4.8.2. Matrix inner product 138 4.8.3. Frobenius norm 138 4.9. Subspaces associated with a matrix 139 4.10. Matrix rank 141 4.10.1. Definition and properties 141 4.10.2. Sum and difference rank 143 4.10.3. Subspaces associated with a matrix product 143 4.10.4. Product rank 144 4.11. Determinant, inverses and generalized inverses 145 4.11.1. Determinant 145 4.11.2. Matrix inversion 148 4.11.3. Solution of a homogeneous system of linear equations 149 4.11.4. Complex matrix inverse 150 4.11.5. Orthogonal and unitary matrices 150 4.11.6. Involutory matrices and anti-involutory matrices 151 4.11.7. Left and right inverses of a rectangular matrix 153 4.11.8. Generalized inverses 155 4.11.9. Moore–Penrose pseudo-inverse 157 4.12. Multiplicative groups of matrices 158 4.13. Matrix associated to a linear map 159 4.13.1. Matrix representation of a linear map 159 4.13.2. Change of basis 162 4.13.3. Endomorphisms 164 4.13.4. Nilpotent endomorphisms 166 4.13.5. Equivalent, similar and congruent matrices 167 4.14. Matrix associated with a bilinear/sesquilinear form 168 4.14.1. Definition of a bilinear/sesquilinear map 168 4.14.2. Matrix associated to a bilinear/sesquilinear form 170 4.14.3. Changes of bases with a bilinear form 170 4.14.4. Changes of bases with a sesquilinear form 171 4.14.5. Symmetric bilinear/sesquilinear forms 172 4.15. Quadratic forms and Hermitian forms 174 4.15.1. Quadratic forms 174 4.15.2. Hermitian forms 176 4.15.3. Positive/negative definite quadratic/Hermitian forms 177 4.15.4. Examples of positive definite quadratic forms 178 4.15.5. Cauchy–Schwarz and Minkowski inequalities 179 4.15.6. Orthogonality, rank, kernel and degeneration of a bilinear form 180 4.15.7. Gauss reduction method and Sylvester’s inertia law 181 4.16. Eigenvalues and eigenvectors 184 4.16.1. Characteristic polynomial and Cayley–Hamilton theorem 184 4.16.2. Right eigenvectors 186 4.16.3. Spectrum and regularity/singularity conditions 187 4.16.4. Left eigenvectors 188 4.16.5. Properties of eigenvectors 188 4.16.6. Eigenvalues and eigenvectors of a regularized matrix 190 4.16.7. Other properties of eigenvalues 190 4.16.8. Symmetric/Hermitian matrices 191 4.16.9. Orthogonal/unitary matrices 193 4.16.10. Eigenvalues and extrema of the Rayleigh quotient 194 4.17. Generalized eigenvalues 195 Chapter 5. Partitioned Matrices 199 5.1. Introduction 199 5.2. Submatrices 200 5.3. Partitioned matrices 201 5.4. Matrix products and partitioned matrices 202 5.4.1. Matrix products 202 5.4.2. Vector Kronecker product 202 5.4.3. Matrix Kronecker product 202 5.4.4. Khatri–Rao product 204 5.5. Special cases of partitioned matrices 205 5.5.1. Block-diagonal matrices 205 5.5.2. Signature matrices 205 5.5.3. Direct sum 205 5.5.4. Jordan forms 206 5.5.5. Block-triangular matrices 206 5.5.6. Block Toeplitz and Hankel matrices 207 5.6. Transposition and conjugate transposition 207 5.7. Trace 208 5.8. Vectorization 208 5.9. Blockwise addition 208 5.10. Blockwise multiplication 209 5.11. Hadamard product of partitioned matrices 209 5.12. Kronecker product of partitioned matrices 210 5.13. Elementary operations and elementary matrices 212 5.14. Inversion of partitioned matrices 214 5.14.1. Inversion of block-diagonal matrices 215 5.14.2. Inversion of block-triangular matrices 215 5.14.3. Block-triangularization and Schur complements 216 5.14.4. Block-diagonalization and block-factorization 216 5.14.5. Block-inversion and partitioned inverse 217 5.14.6. Other formulae for the partitioned 2 × 2 inverse 218 5.14.7. Solution of a system of linear equations 219 5.14.8. Inversion of a partitioned Gram matrix 220 5.14.9. Iterative inversion of a partitioned square matrix 220 5.14.10. Matrix inversion lemma and applications 221 5.15. Generalized inverses of 2 × 2 block matrices 222 5.16. Determinants of partitioned matrices 224 5.16.1. Determinant of block-diagonal matrices 224 5.16.2. Determinant of block-triangular matrices 225 5.16.3. Determinant of partitioned matrices with square diagonal blocks 225 5.16.4. Determinants of specific partitioned matrices 226 5.16.5. Eigenvalues of CB and BC 227 5.17. Rank of partitioned matrices 228 5.18. Levinson–Durbin algorithm 229 5.18.1. AR process and Yule–Walker equations 230 5.18.2. Levinson–Durbin algorithm 232 5.18.3. Linear prediction 237 Chapter 6. Tensor Spaces and Tensors 243 6.1. Chapter summary 243 6.2. Hypermatrices 243 6.2.1. Hypermatrix vector spaces 244 6.2.2. Hypermatrix inner product and Frobenius norm 245 6.2.3. Contraction operation and n-mode hypermatrix–matrix product 245 6.3. Outer products 249 6.4. Multilinear forms, homogeneous polynomials and hypermatrices 251 6.4.1. Hypermatrix associated to a multilinear form 251 6.4.2. Symmetric multilinear forms and symmetric hypermatrices 252 6.5. Multilinear maps and homogeneous polynomials 255 6.6. Tensor spaces and tensors 255 6.6.1. Definitions 255 6.6.2. Multilinearity and associativity 257 6.6.3. Tensors and coordinate hypermatrices 257 6.6.4. Canonical writing of tensors 258 6.6.5. Expansion of the tensor product of N vectors 260 6.6.6. Properties of the tensor product 261 6.6.7. Change of basis formula 266 6.7. Tensor rank and tensor decompositions 268 6.7.1. Matrix rank 268 6.7.2. Hypermatrix rank 268 6.7.3. Symmetric rank of a hypermatrix 269 6.7.4. Comparative properties of hypermatrices and matrices 269 6.7.5. CPD and dimensionality reduction 271 6.7.6. Tensor rank 273 6.8. Eigenvalues and singular values of a hypermatrix 274 6.9. Isomorphisms of tensor spaces 276 References 281 Index 291

Read more less

Book SynopsisMathematical morphology has developed a powerful methodology for segmenting images, based on connected filters and watersheds. We have chosen the abstract framework of node- or edge-weighted graphs for an extensive mathematical and algorithmic description of these tools. Volume 1 is devoted to watersheds. The topography of a graph appears by observing the evolution of a drop of water moving from node to node on a weighted graph, along flowing paths, until it reaches regional minima. The upstream nodes of a regional minimum constitute its catchment zone. The catchment zones may be constructed independently of each other and locally, in contrast with the traditional approach where the catchment basins have to be constructed all at the same time. Catchment zones may overlap, and thus, a new segmentation paradigm is proposed in which catchment zones cover each other according to a priority order. The resulting partition may then be corrected, by local and parallel treatments, in order to achieve the desired precision. Table of ContentsNotations xiii Introduction xxvii Part 1. Getting Started 1 Chapter 1. A Primer to Flooding, Razing and Watersheds 3 1.1. Topographic reliefs and topographic features 3 1.1.1. Images seen as topographic reliefs and inversely 3 1.1.2. Topographic features 5 1.1.3. Modeling a topographic relief as a weighted graph 8 1.2. Flooding, razing and morphological filters 10 1.2.1. The principle of duality 10 1.2.2. Dominated flooding and razing 10 1.2.3. Flooding, razing and catchment zones of a topographic relief 16 1.3. Catchment zones of flooded surfaces 18 1.3.1. Filtering and segmenting 18 1.3.2. Reducing the oversegmentation with markers 19 1.4. The waterfall hierarchy 26 1.4.1. Overflows between catchment basins 26 1.5. Size-driven hierarchies 28 1.6. Separating overlapping particles in n dimensions 31 1.7. Catchment zones and lakes of region neighborhood graphs 33 1.8. Conclusion 37 Chapter 2. Watersheds and Flooding: a Segmentation Golden Braid 39 2.1. Watersheds, offsprings and parallel branches 40 2.2. Flooding and connected operators 43 2.3. Connected operators and hierarchies 45 2.4. Hierarchical segmentation: extinction values 47 Chapter 3. Mathematical Notions 49 3.1. Summary of the chapter 49 3.2. Complete lattices 49 3.2.1. Partial order and partially ordered sets 49 3.2.2. Upper and lower bounds 50 3.2.3. Complete lattices 50 3.2.4. Dyadic relations on a complete lattice 51 3.3. Operators between complete lattices 51 3.3.1. Definition of an operator 51 3.3.2. Properties of the operators 52 3.3.3. Erosion and dilation 52 3.3.4. Opening and closing 53 3.4. The adjunction: a cornerstone of mathematical morphology 53 3.4.1. Adjoint erosions and dilations 53 3.4.2. Increasingness 53 3.4.3. Unicity 53 3.4.4. Composition 54 3.4.5. Dual operators 54 3.5. Openings and closings 54 3.5.1. Definitions 54 3.5.2. Elements with the same erosion or the same dilation 55 3.5.3. The invariants of an opening or a closing 55 3.6. Complete lattices of functions 55 3.6.1. Definitions 55 3.6.2. Infimum and supremum 56 Part 2. The Topography of Weighted Graphs 57 Chapter 4. Weighted Graphs 59 4.1. Summary of the chapter 59 4.2. Reminders on graphs 60 4.2.1. Directed and undirected graphs 60 4.3. Weight distributions on the nodes or edges of a graph 62 4.3.1. Duality 63 4.3.2. Erosions and dilations, openings, closings 63 4.3.3. Labels 66 4.4. Exploring the topography of graphs by following a drop of water 66 4.5. Node-weighted graphs 67 4.5.1. Flat zones and regional minima 67 4.5.2. Flowing paths and catchment zones 67 4.6. Edge-weighted graphs 69 4.6.1. Flat zones and regional minima 69 4.6.2. Flowing paths and catchment zones 69 4.6.3. Even zones and regional minima 71 4.7. Comparing the topography of node-weighted graphs and edge-weighted graphs 72 Chapter 5. Flowing Graphs 73 5.1. Summary of the chapter 73 5.2. Towards a convergence between node- and edge-weighted graphs 74 5.2.1. The flowing edges in a node-weighted graph G(ν, nil) 74 5.2.2. The flowing edges in an edge-weighted graph G(nil, η) 75 5.2.3. Flowing graphs 76 5.3. The flowing adjunction 76 5.4. Flowing edges under closer scrutiny 77 5.4.1. Relations between the flowing edges of G(ν, nil) and G(nil, δenν) 77 5.4.2. Relations between the flowing edges of G(nil, η) and G(εneη, nil) 78 5.4.3. Chaining the inclusions between flowing edges 78 5.4.4. Criteria characterizing flowing graphs 79 5.4.5. Transforming a node- or edge-weighted graph into a flowing graph 81 5.4.6. The invariance domains of γe and ϕn 83 5.4.7. Particular flowing graphs 87 5.5. Illustration as a hydrographic model 88 5.5.1. A hydrographic model of tanks and pipes 88 5.5.2. Associating an “edge unstable” tank network with an arbitrary node-weighted graph G(ν, nil) 90 5.5.3. Associating a “node unstable” tank network with an arbitrary edge-weighted graph G(nil, η) 91 5.5.4. Chaining the operations 92 Chapter 6. The Topography of Digraphs 97 6.1. Summary of the chapter 97 6.1.1. General digraphs 98 6.1.2. Digraphs without perpetuum mobile configurations 98 6.2. Status report 98 6.2.1. Case of node-weighted graphs 99 6.2.2. Case of edge-weighted graphs 99 6.3. The topography of unweighted digraphs 100 6.3.1. Notations 100 6.3.2. Smooth zones, dead ends, flat zones and black holes of digraphs 101 6.4. The topography of gravitational digraphs 105 6.4.1. No “perpetuum mobile” 105 6.4.2. Defining and propagating labels 107 6.4.3. A dead leaves model of catchment zones 113 6.4.4. Examples of gravitational graphs 122 6.4.5. The topography of weighted graphs interpreted in the light of the derived digraphs 122 Part 3. Reducing the Overlapping of Catchment Zones 125 Chapter 7. Measuring the Steepness of Flowing Paths 127 7.1. Summary of the chapter 127 7.2. Why do the catchment zones overlap? 128 7.2.1. Relation between the catchment zones and the flowing paths 128 7.2.2. Comparing the steepness of flowing paths 128 7.2.3. The redundancy between node and edge weights 129 7.2.4. General flow digraphs 130 7.3. The lexicographic pre-order relation of length k 131 7.3.1. Prolonging flowing paths into paths of infinite length 131 7.3.2. Comparing the steepness of two flowing paths 132 7.3.3. Properties of ∞ − steep paths 134 Chapter 8. Pruning a Flow Digraph 137 8.1. Summary of the chapter 137 8.1.1. Transforming a node- or edge-weighted graph into a node-weighted flowing digraph (reminder) 137 8.1.2. Global pruning 138 8.1.3. Local pruning 138 8.2. The pruning operator 138 8.2.1. Two operators on flow digraphs 139 8.2.2. Pruning by concatenating both operators 140 8.2.3. Properties of pruning 142 8.2.4. A variant of pruning 146 8.2.5. Local pruning 8.3. Evolution of catchment zones with pruning 147 8.3.1. Analyzing a digital elevation model 148 Chapter 9. Constructing an ∞ - steep Digraph by Flooding 155 9.1. Summary of the chapter 155 9.2. Characterization of ∞ − steep graphs 156 9.3. The core-expanding flooding algorithm 156 9.3.1. The first version of the core-expanding algorithm 157 9.3.2. The second version of the core-expanding algorithm 160 9.3.3. The third version of the core-expanding algorithm 164 9.3.4. The last version of the core-expanding algorithm, constructing a partial ∞ − steep flowing graph 167 Chapter 10. Creating Steep Watershed Partitions 169 10.1. Summary of the chapter 169 10.2. Creating watershed partitions with the core-expanding algorithm 169 10.2.1. Illustration of the HQ algorithm applied to node-weighted graphs 171 10.3. Propagating labels while pruning the digraph 172 10.3.1. Constructing a watershed partition during pruning 173 10.4. Pruning or flooding: two ways for catchment zones to grow 176 Chapter 11. An Historical Intermezzo 179 11.1. Watersheds: the early days 179 11.1.1. The level-by-level construction of watersheds 180 11.1.2. A hierarchical queue watershed algorithm 181 11.2. A watershed as the SKIZ for the topographic distance 181 11.2.1. The topographic distance 181 11.3. Convergence into a unique algorithm of three research streams 182 11.3.1. Three formulations of watershed partitions, one algorithm 182 11.3.2. Discussion 183 Part 4. Segmenting with Dead Leaves Partitions 185 Chapter 12. Intermezzo: Encoding the Digraph Associated with an Image 187 12.1. Summary of the theoretical developments seen so far 187 12.2. Summary of the chapter 188 12.3. Representing a node-weighted digraph as two images 188 12.3.1. The encoding of the digraph associated with an image 188 12.3.2. Operators acting on node-weighted digraphs 190 12.4. Defining labels 192 12.4.1. Operators on unweighted unlabeled digraphs 193 12.4.2. Operators on labeled unweighted digraphs 194 12.4.3. Operators on weighted and labeled digraphs 198 Chapter 13. Two Paradigms for Creating a Partition or a Partial Partition on a Graph 203 13.1. Summary of the chapter 203 13.2. Setting up a common stage for node- and edge-weighted graphs 203 13.3. A brief tool inventory 204 13.3.1. Operators making no use of the node weights 204 13.3.2. Operators propagating labels 204 13.3.3. Operators making use of the node weights and the graph structure 205 13.4. Dead leaves tessellations versus tilings: two paradigms 205 13.5. Extracting catchment zones containing a particular node 206 13.5.1. Core expansion versus pruning algorithms 206 13.5.2. Illustration of the pruning algorithm 207 13.6. Catchment zones versus catchment basins 209 Chapter 14. Dead Leaves Segmentation 211 14.1. Summary of the chapter 211 14.2. Segmenting with a watershed 211 14.2.1. Segmenting with watershed partitions 211 14.2.2. A crossroad of several methods 213 14.3. The evolution of a dead leaves tessellation with pruning 214 14.4. Local correction of overlapping zones 217 14.4.1. Pruning analysis 217 14.4.2. Local pruning for reducing overlapping zones 219 14.4.3. A local core-expanding algorithm for reducing overlapping zones 221 14.5. Local correction of the overlapping zones on a DEM 221 14.5.1. Local core-expanding algorithm for reducing overlapping zones 225 14.5.2. Advantage of the two-step construction of a dead leaves tessellation 227 14.6. Segmentation of some marked regions 231 14.6.1. Segmenting the domain and extracting the objects of interest 232 14.6.2. Extraction of the marked catchment zones and local correction of errors 233 Chapter 15. Propagating Segmentations 241 15.1. Summary of the chapter 241 15.2. Step-by-step segmentation 241 15.2.1. Principle of the method 241 15.2.2. Segmentation of blood cells 242 15.2.3. Segmentation of an electronic circuit 243 15.3. Marker-based segmentation 245 Appendix 247 References 259 Index 267

Read more less

Book SynopsisThis book uses MATLAB as a computing tool to explore traditional DSP topics and solve problems. This greatly expands the range and complexity of problems that students can effectively study in signal processing courses. A large number of worked examples, computer simulations and applications are provided, along with theoretical aspects that are essential in order to gain a good understanding of the main topics. Practicing engineers may also find it useful as an introductory text on the subject.Table of ContentsChapter 1. Introduction. Chapter 2. 1-D and 2-D discrete-time signals. Chapter 3. Discrete-time random processes. Chapter 4. Statistics for signal processing. Chapter 5. Convolution of 1-D and 2-D signals. Chapter 6. Discrete Fourier transform of 1-D and 2-D discrete signals. Chapter 7. Linear and invariant disctrete-time systems. Chapter 8. Infinite impulse response filters. Chapter 9. Finite impulse response filters. Chapter 10. Digital modulations. Chapter 11. Statistical signal processing: estimation. Chapter 12. Power spectrum density estimation. Chapter 13. Time-frequency spectral estimation. Chapter 14. Model-based time-frequency spectral estimation. Chapter 15. Statistical signal processing: classification. Chapter 16. Data compression. Chapter 17. Programming digital signal processors with MATLAB. List of Authors. Index.

Read more less

Book SynopsisThis book focuses on signal processing algorithms based on the timefrequency domain. Original methods and algorithms are presented which are able to extract information from non-stationary signals such as heart sounds and power electric signals. The methods proposed focus on the time-frequency domain, and most notably the Stockwell Transform for the feature extraction process and to identify signatures. For the classification method, the Adaline Neural Network is used and compared with other common classifiers. Theory enhancement, original applications and concrete implementation on FPGA for real-time processing are also covered in this book.Table of ContentsPreface ix Chapter 1. The Need for Time–Frequency Analysis 1 1.1. Introduction 1 1.2. Stationary and non-stationary concepts 2 1.2.1. Stationarity 2 1.2.2. Non-stationarity 4 1.3. Temporal representations 5 1.4. Frequency representations of signals 6 1.4.1. Fourier transform 7 1.4.2. Mean frequency, bandwidth and frequency average 10 1.5. Uncertainty principle 12 1.6. Limitation of time analysis and frequency analysis: the need for time–frequency representation 15 1.6.1. Instantaneous frequency 15 1.7. Conclusion 18 1.8. Bibliography 19 Chapter 2. Time–Frequency Analysis: The S-Transform 21 2.1. Introduction 21 2.2. Synthetic signals 22 2.3. The STFT 22 2.4. The WT 24 2.5. The Wigner–Ville distribution 25 2.5.1. The pseudo-WVD 27 2.5.2. The smoothed PWVD 27 2.6. Cohen’s class 28 2.7. The S-transform 29 2.7.1. Properties of the S-transform 30 2.7.2. The discrete S-transform 38 2.7.3. The improvement of the S-transform energy concentration 41 2.7.4. The ST-spectrogram 51 2.8. Conclusion 56 2.9. Bibliography 56 Chapter 3. Segmentation and Classification of Heart Sounds Based on the S-Transform 61 3.1. Introduction 61 3.2. Methods and materials 64 3.2.1. Data sets 64 3.2.2. Localization and segmentation of heart sounds 65 3.2.3. Classification of heart sounds 70 3.3. Results and discussion 73 3.3.1. Localization and segmentation results 73 3.3.2. S1 and S2 classification results 77 3.3.3. Murmur detection results 80 3.4. Conclusion 82 3.5. Bibliography 83 Chapter 4. Adaline for the Detection of Electrical Events in Electrical Signals 87 4.1. Introduction 87 4.2. Electric events 88 4.2.1. Power quality 88 4.2.2. Electric events 89 4.3. Adaline 90 4.4. Adaline for frequency estimation 91 4.4.1. Adaline method 91 4.4.2. Results 94 4.5. Adaline for voltage component extraction in unbalanced system 97 4.5.1. Model of the unbalanced voltage system 98 4.5.2. Extraction of the voltage components in the DQ-space 99 4.5.3. Online estimation of the instantaneous phases θd and θi 100 4.5.4. Filtering the AC components in the DQ-space 101 4.5.5. Results 104 4.6. Adaline for harmonic current identification and compensation 108 4.6.1. Adaline method 110 4.6.2. Results 115 4.7. Conclusion 117 4.8. Bibliography 118 Chapter 5. FPGA Implementation of the Adaline 121 5.1. Introduction 121 5.2. Instantaneous power theory (IPT) in the APF 122 5.3. Adaline for the computing of the IPT in the PLL 123 5.3.1. Adaline-based PLL 123 5.3.2. A multiplexing approach for hardware consumption reduction 126 5.4. Results 129 5.4.1. Simulation 129 5.4.2. FPGA implementation results 130 5.5. Conclusion 132 5.6. Bibliography 133 Index 135

Read more less

Book SynopsisThe focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on the basis of observed data. The building of solutions involves the recognition of other pieces of a priori information. These solutions are then specific to the pieces of information taken into account. Clarifying and taking these pieces of information into account is necessary for grasping the domain of validity and the field of application for the solutions built. For too long, the interest in these problems has remained very limited in the signal-image community. However, the community has since recognized that these matters are more interesting and they have become the subject of much greater enthusiasm. From the application field’s point of view, a significant part of the book is devoted to conventional subjects in the field of inversion: biological and medical imaging, astronomy, non-destructive evaluation, processing of video sequences, target tracking, sensor networks and digital communications. The variety of chapters is also clear, when we examine the acquisition modalities at stake: conventional modalities, such as tomography and NMR, visible or infrared optical imaging, or more recent modalities such as atomic force imaging and polarized light imaging.Table of ContentsINTRODUCTION xiJean-Francois GIOVANNELLI and Jerome IDIER CHAPTER 1. 3D RECONSTRUCTION IN X-RAY TOMOGRAPHY: APPROACH EXAMPLE FOR CLINICAL DATA PROCESSING 1Yves GOUSSARD 1.1. Introduction 1 1.2. Problem statement 2 1.3. Method 7 1.4. Results 15 1.5. Conclusion 26 1.6. Acknowledgments 27 1.7. Bibliography 28 CHAPTER 2. ANALYSIS OF FORCE-VOLUME IMAGES IN ATOMIC FORCE MICROSCOPY USING SPARSE APPROXIMATION 31Charles SOUSSEN, David BRIE, Gregory FRANCIUS, Jerome IDIER 2.1. Introduction 31 2.2. Atomic force microscopy 32 2.3. Data processing in AFM spectroscopy 40 2.4. Sparse approximation algorithms 43 2.5. Real data processing 49 2.6. Conclusion 52 2.7. Bibliography 53 CHAPTER 3. POLARIMETRIC IMAGE RESTORATION BY NON-LOCAL MEANS 57Sylvain FAISAN, Francois ROUSSEAU, Christian HEINRICH, Jihad ZALLAT 3.1. Introduction 57 3.2. Light polarization and the Stokes–Mueller formalism 58 3.3. Estimation of the Stokes vectors 61 3.4. Results 72 3.5. Conclusion 77 3.6. Bibliography 78 CHAPTER 4. VIDEO PROCESSING AND REGULARIZED INVERSION METHODS 81Guy LE BESNERAIS, Frederic CHAMPAGNAT 4.1. Introduction 81 4.2. Three applications 82 4.3. Dense image registration 88 4.4. A few achievements based on direct formulation 92 4.5. Conclusion 104 4.6. Bibliography 106 CHAPTER 5. BAYESIAN APPROACH IN PERFORMANCE MODELING: APPLICATION TO SUPERRESOLUTION 109Frederic CHAMPAGNAT, Guy LE BESNERAIS, Caroline KULCSAR 5.1. Introduction 109 5.2. Performance modeling and Bayesian paradigm 111 5.3. Superresolution techniques behavior 113 5.4. Application examples 126 5.5. Real data processing 130 5.6. Conclusion 136 5.7. Bibliography 137 CHAPTER 6. LINE SPECTRA ESTIMATION FOR IRREGULARLY SAMPLED SIGNALS IN ASTROPHYSICS 141Sebastien BOURGUIGNON, Herve CARFANTAN 6.1. Introduction 141 6.2. Periodogram, irregular sampling, maximum likelihood 144 6.3. Line spectra models: spectral sparsity 146 6.4. Prewhitening, CLEAN and greedy approaches 151 6.5. Global approach and convex penalization 155 6.6. Probabilistic approach for sparsity 159 6.7. Conclusion 164 6.8. Bibliography 165 CHAPTER 7. JOINT DETECTION-ESTIMATION IN FUNCTIONAL MRI 169Philippe CIUCIU, Florence FORBES, Thomas VINCENT, Lotfi CHAARI 7.1. Introduction to functional neuroimaging 169 7.2. Joint detection-estimation of brain activity 171 7.3. Bayesian approach 178 7.4. Scheme for stochastic MCMC inference 183 7.5. Alternative variational inference scheme 184 7.6. Comparison of both types of solutions 190 7.7. Conclusion 194 7.8. Bibliography 195 CHAPTER 8. MCMC AND VARIATIONAL APPROACHES FOR BAYESIAN INVERSION IN DIFFRACTION IMAGING 201Hacheme AYASSO, Bernard DUCHENE, Ali MOHAMMAD-DJAFARI 8.1. Introduction 201 8.2. Measurement configuration 204 8.3. The forward model 206 8.4. Bayesian inversion approach 211 8.5. Results 220 8.6. Conclusions 220 8.7. Bibliography 222 CHAPTER 9. VARIATIONAL BAYESIAN APPROACH AND BI-MODEL FOR THE RECONSTRUCTION-SEPARATION OF ASTROPHYSICS COMPONENTS 225Thomas RODET, Aurelia FRAYSSE, Hacheme AYASSO 9.1. Introduction 225 9.2. Variational Bayesian methodology 228 9.3. Exponentiated gradient for variational Bayesian 229 9.4. Application: reconstruction-separation of astrophysical components 232 9.5. Implementation of the variational Bayesian approach 236 9.6. Results 240 9.7. Conclusion 246 9.8. Bibliography 246 CHAPTER 10. KERNEL VARIATIONAL APPROACH FOR TARGET TRACKING IN A WIRELESS SENSOR NETWORK 251Hichem SNOUSSI, Paul HONEINE, Cedric RICHARD 10.1. Introduction 251 10.2. State of the art: limitations of existing methods 252 10.3. Model-less target tracking 254 10.4. Simulation results 261 10.5. Conclusion 264 10.6. Bibliography 264 CHAPTER 11. ENTROPIES AND ENTROPIC CRITERIA 267Jean-Francois BERCHER 11.1. Introduction 267 11.2. Some entropies in information theory 268 11.3. Source coding with escort distributions and Renyi bounds 273 11.4. A simple transition model 277 11.5. Minimization of the Renyi divergence and associated entropies 281 11.6. Bibliography 289 LIST OF AUTHORS 293 INDEX 297

Read more less

Book SynopsisVolume 3 of the second edition of the fully revised and updated Digital Signal and Image Processing using MATLAB, after first two volumes on the "Fundamentals" and "Advances and Applications: The Deterministic Case", focuses on the stochastic case. It will be of particular benefit to readers who already possess a good knowledge of MATLAB, a command of the fundamental elements of digital signal processing and who are familiar with both the fundamentals of continuous-spectrum spectral analysis and who have a certain mathematical knowledge concerning Hilbert spaces. This volume is focused on applications, but it also provides a good presentation of the principles. A number of elements closer in nature to statistics than to signal processing itself are widely discussed. This choice comes from a current tendency of signal processing to use techniques from this field. More than 200 programs and functions are provided in the MATLAB language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.Table of ContentsForeword ix Notations and Abbreviations xiii 1 Mathematical Concepts 1 1.1 Basic concepts on probability 1 1.2 Conditional expectation 9 1.3 Projection theorem 10 1.4 Gaussianity 13 1.5 Random variable transformation 18 1.6 Fundamental statistical theorems 21 1.7 Other important probability distributions 23 2 Statistical Inferences 25 2.1 Statistical model 25 2.2 Hypothesis tests 27 2.3 Statistical estimation 41 3 Monte-Carlo Simulation 85 3.1 Fundamental theorems 85 3.2 Stating the problem 86 3.3 Generating random variables 88 3.4 Variance reduction 99 4 Second Order Stationary Process 107 4.1 Statistics for empirical correlation 107 4.2 Linear prediction of WSS processes 111 4.3 Non-parametric spectral estimation of WSS processes 124 5 Inferences on HMM 139 5.1 Hidden Markov Models (HMM) 130 5.2 Inferences on HMM 142 5.3 Gaussian linear case: the Kalman filter 143 5.4 Discrete finite Markov case 152 6 Selected Topics 163 6.1 High resolution methods 163 6.2 Digital Communications 186 6.3 Linear equalization and the Viterbi algorithm 211 6.4 Compression 220 7 Hints and Solutions 235 H1 Mathematical concepts 235 H2 Statistical inferences 237 H3 Monte-Carlo simulation 269 H4 Second order stationary process 283 H5 Inferences on HMM 283 H6 Selected Topics 300 8 Appendices 317 A1 Miscellaneous functions 317 A2 Statistical functions 318 Bibliography 329 Index 333

Read more less

Book SynopsisThis book covers the fundamentals of digital signal processing (DSP) in a concise format, accessible to anyone with a technical background, enabling the reader for further DSP training, research, and development. The authors explore many subjects, including discrete time (digital) signals and systems, with emphasis on linear shift invariant (LSI) systems; Fourier and the z transforms; signal sampling and analog-to-digital (A/D) conversion. The book ends with examples of DSP techniques applications to practical problems from several areas.

Read more less

Book SynopsisThis textbook provides comprehensive coverage for courses in the basics of design and implementation of digital filters. The book assumes only basic knowledge in digital signal processing and covers state-of-the-art methods for digital filter design and provides a simple route for the readers to design their own filters. The advanced mathematics that is required for the filter design is minimized by providing an extensive MATLAB toolbox with over 300 files. The book presents over 200 design examples with MATLAB code and over 300 problems to be solved by the reader. The students can design and modify the code for their use. The book and the design examples cover almost all known design methods of frequency-selective digital filters as well as some of the authors’ own, unique techniques. Table of ContentsIntroduction.- Signals and Transforms.- Discrete-Time and Digital Filters.- Filter Algorithms.- Finite Wordlength Effects.- Synthesis of Fir Filters.- Realization of Fir Filters.- Synthesis of Analog Filters.- Analog Filters with Lumped and Distributed Elements.- Synthesis of IIR Filters.- Wave Digital Filters.- Ladder Wave Digital Filters.- Symmetric Wave Digital Filters.- Frequency-Response Masking Filters.- Sampling Rate Converters.- Multirate Filters.- Implementation of Digital Filters.- References.- Index.

Read more less

Book SynopsisThis comprehensive reference provides easy access to relevant information on all aspects of Computer Vision. An A-Z format of over 240 entries offers a diverse range of topics for those seeking entry into any aspect within the broad field of Computer Vision. Over 200 Authors from both industry and academia contributed to this volume.Each entry includes synonyms, a definition and discussion of the topic, and a robust bibliography. Extensive cross-references to other entries support efficient, user-friendly searches for immediate access to relevant information. Entries were peer-reviewed by a distinguished international advisory board, both scientifically and geographically diverse, ensuring balanced coverage. Over 3700 bibliographic references for further reading enable deeper exploration into any of the topics covered.The content of Computer Vision: A Reference Guide is expository and tutorial, making the book a practical resource for students who are considering entering the field, as well as professionals in other fields who need to access this vital information but may not have the time to work their way through an entire text on their topic of interest.Table of ContentsOver 240 entries organized A to Z.

Read more less

Book SynopsisThis book presents applications of cognitive management and cognitive computing in the fields of risk management, cognitive fraud detection, and in business decision making. The book provides insights on how cognitive management and cognitive computing enable businesses to quickly augment human intelligence and help humans perform tasks better. For example, the authors describe how by analyzing patterns in big data, small data, and "dark data," cognitive technologies can detect human behavior and suggest options for personalizing of products and services. The book studies companies in industries such as automotive, airline, health care, retail, wealth management, and litigation who have adopted these approaches. Presents applications of cognitive computing and cognitive management used in augmenting and empowering business decisions; Shows how to employ the Internet of Things in businesses using a cognitive management framework; Discusses technical aspects and alternatives to traditional tools, algorithms, and methodologies in cognitive computing. Table of ContentsIntroduction.- Cognitive Management.- Applications of Cognitive Computing for risk management.- Managing organizational mind by cognitive management.- Cognitive Managerial Approach towards Employee Participation in Management.- Role of Cognitive Computing in Business and Management.- The cognitive approach to Entrepreneurship.- Empowering the Internet of Things using Cognitive Management Framework.- Social Cognitive Theory in Multidisciplinary research.- Convergence of Cognitive Management and Cognitive Computing in the information society context.- Cognitive Computing and Knowledge Management.- Conclusion.

Read more less

Book SynopsisThis book is intended to be a little different from other books in its coverage. There are a great many digital signal processing (DSP) books and signals and systems books on the market. Since most undergraduate courses begin with signals and systems and then move on in later years to DSP, I felt a need to combine the two into one book that was concise yet not too overburdening. This means that students need only purchase one book instead of two and at the same time see the flow of knowledge from one subject into the next. Like the rudiments of music, it starts at the very beginning with some elementary knowledge and builds on it chapter by chapter to advanced work by chapter 15. I have been teaching now for 38 years and always think it necessary to credit the pioneers of the subjects we teach and ask the question “How did we get to this present stage in technological achievement”? Therefore, in Chapter 1 I have given a concise history trying to not sway too much away from the subject area. This is followed by the rudimentary theory in increasing complexity. It has already been taught successfully to a class at Auckland University of Technology New Zealand.Table of ContentsFrom the content: Introduction and basic signal properties.- Dynamic systems introduction.- Further introductory topics in Signals and Systems.- Frequency-domain properties of signals.- Sampling of signals and discrete mathematical methods.- Properties of discrete-time systems and signals.- A more complete picture.- FIR Filter design.

Read more less

Book SynopsisThis book celebrates binocular vision by presenting illustrations that require two eyes to see the effects of cooperation and competition between them. Pictures are flat but by printing them in different colours and viewing them through similarly coloured filters (included with the hardcover book) they are brought to life either in stereoscopic depth or in rivalry with one another. They are called anaglyphs and all those in the book display the ways in which the eyes interact. Thus, the reader is an integral element in the book and not all readers will see the same things. The history, science and art of binocular vision can be experienced in ways that are not usually available to us and with images made specifically for this book. The study of vision with two eyes was transformed by the invention of stereoscopes in the early 19th century. Anaglyphs are simple forms of stereoscopes that have three possible outcomes from viewing them – with each eye alone to see the monocular images, with both eyes to see them in stereoscopic depth or rivalry, or without the red/cyan glasses where they can have an appeal independent of the binocularity they encompass. Through the binocular pictures and the words that accompany them there will be an appreciation of just how remarkable the processes are that yield binocular singleness and depth. Moreover, the opportunities for expressing these processes are explored with many examples of truly binocular art. Table of ContentsSetting the seen.- A little history.- Binocular vision.- Stereoscopes.- Stereoscopic vision.- Binocular rivalry.- Binocular controversies.- Binocular art.- Conclusion.

Read more less

Book SynopsisThis textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from scratch. It provides a treatment of the general recurrent neural networks with principled methods for training that render the (generalized) backpropagation through time (BPTT). This author focuses on the basics and nuances of recurrent neural networks, providing technical and principled treatment of the subject, with a view toward using coding and deep learning computational frameworks, e.g., Python and Tensorflow-Keras. Recurrent neural networks are treated holistically from simple to gated architectures, adopting the technical machinery of adaptive non-convex optimization with dynamic constraints to leverage its systematic power in organizing the learning and training processes. This permits the flow of concepts and techniques that provide grounded support for design and training choices. The author’s approach enables strategic co-training of output layers, using supervised learning, and hidden layers, using unsupervised learning, to generate more efficient internal representations and accuracy performance. As a result, readers will be enabled to create designs tailoring proficient procedures for recurrent neural networks in their targeted applications.Table of ContentsIntroduction1. Network Architectures2. Learning Processes3. Recurrent Neural Networks (RNN)4. Gated RNN: The Long Short-Term Memory (LSTM) RNN5. Gated RNN: The Gated Recurrent Unit (GRU) RNN6. Gated RNN: The Minimal Gated Unit (MGU) RNN

Read more less

Book SynopsisThis textbook is a concise yet precise supplement to traditional books on Signals and Systems, focusing exclusively on the continuous-time case. Students can use this guide to review material, reinforce their understanding, and see how all the parts connect together in a uniform treatment focused on mathematical clarity. Readers learn the “what”, “why” and “how” about the ubiquitous Fourier and Laplace transforms encountered in the study of linear time-invariant systems in engineering: what are these transforms, why do we need them, and how do we use them? Readers will come away with an understanding of the gradual progression from time-domain analysis to frequency-domain and s-domain techniques for continuous-time linear time-invariant systems. This book reflects the author’s experience in teaching this material for over 25 years in sophomore- and junior-level required engineering courses and is ideal for undergraduate classes in electrical engineering.Table of Contents1. Introduction2. Systems3. Periodic Signals and Fourier Series4. Analysis of Stable Systems using the Fourier Transform5. Sampling and Reconstruction6. Analysis and Control of Systems using the Laplace Transform

Read more less

Book SynopsisThis SpringerBrief presents novel methods of approaching challenging problems in the reconstruction of accurate 3D models and serves as an introduction for further 3D reconstruction methods. It develops a 3D reconstruction system that produces accurate results by cascading multiple novel loop detection, sifting, and optimization methods.The authors offer a fast point cloud registration method that utilizes optimized randomness in random sample consensus for surface loop detection. The text also proposes two methods for surface-loop sifting. One is supported by a sparse-feature-based optimization graph. This graph is more robust to different scan patterns than earlier methods and can cope with tracking failure and recovery. The other is an offline algorithm that can sift loop detections based on their impact on loop optimization results and which is enabled by a dense map posterior metric for 3D reconstruction and mapping performance evaluation works without any costly ground-truth data. The methods presented in Towards Optimal Point Cloud Processing for 3D Reconstruction will be of assistance to researchers developing 3D modelling methods and to workers in the wide variety of fields that exploit such technology including metrology, geological animation and mass customization in smart manufacturing.Table of Contents1. Introduction.- 2. Preliminaries.- 3. Fractional-Order Random Sample Consensus.- 4. Online Sifting of Loop Detections for 3D Reconstruction of Caves.- 5. Dense Map Posterior: A Novel Quality Metric for 3D Reconstruction.- 6. Offline Sifting and Majorization of Loop Detections.- 7. Conclusion and Future Opportunities.- Appendix: More Information on Results Reproducibility.

Read more less

Book SynopsisThis book provides a comprehensive introduction to all major topics in digital signal processing (DSP). The book is designed to serve as a textbook for courses offered to undergraduate students enrolled in electrical, electronics, and communication engineering disciplines. The text is augmented with many illustrative examples for easy understanding of the topics covered. Every chapter contains several numerical problems with answers followed by question-and-answer type assignments. The detailed coverage and pedagogical tools make this an ideal textbook for students and researchers enrolled in electrical engineering and related programs. Table of ContentsChapter 1. Representation of Discrete Signals and Systems.- Chapter 2. Discrete and Fast Fourier Transforms (DFT and FFT).- Chapter 3. Design of IIR Digital Filters.- Chapter 4. Finite Impulse Response (FIR) Filter Design.- Chapter 5. Finite Word Length Effects.Chapter 6. Multi-rate Digital Signal Processing.

Read more less

Book SynopsisThis book provides a comprehensive guide to 3D Light-Field camera based imaging, exploring the working principles, developments and its applications in fluid mechanics and aerodynamics measurements. It begins by discussing the fundamentals of Light-Field imaging and theoretical resolution analysis, before touching upon the detailed optics design and micro-lens array assembly. Subsequently, Light-Field calibration methods that compensate for optical distortions and establish the relations between the image and real-word 3D coordinates are covered. This is followed by Light-Field 3D reconstruction algorithms which are elaborated for micrometer-scale particles and centimeter-scale physical models. Last but not least, implementations of the preceding procedures to selected fundamental and applied flow measurement scenarios are provided at the end of the book. Development and Application of Light-Field Cameras in Fluid Measurements gives an in-depth analysis of each topic discussed, making it ideal as both an introductory and reference guide for researchers and postgraduates interested in 3D flow measurements.Table of ContentsIntroduction.- Light-field camera working principles.- Volumetric calibration for light-field camera with regular and scheimpflug lens.- Light-field particle image velocimetry.- Simultaneous 3D surface geometry and pressure distribution measurement.- Light-field PIV implementation and case studies.- Future developments of Light-field based measurements.

Read more less

Book SynopsisThis book discusses the Versatile Video Coding (VVC), the ISO and ITU state-of-the-art video coding standard. VVC reaches a compression efficiency significantly higher than its predecessor standard (HEVC) and it has a high versatility for efficient use in a broad range of applications and different types of video content, including Ultra-High Definition (UHD), High-Dynamic Range (HDR), screen content, 360º videos, and resolution adaptivity. The authors introduce the novel VVC tools for block partitioning, intra-frame and inter-frames predictions, transforms, quantization, entropy coding, and in-loop filtering. The authors also present some solutions exploring VVC encoding behavior at different levels to accelerate the intra-frame prediction, applying statistical-based heuristics and machine learning (ML) techniques.Table of ContentsIntroduction.- Versatile Video Coding.- VVC Intra-Frame Prediction.- State-of-the-Art Overview.- Performance Analysis of VVC Intra-Frame Prediction.- Heuristic Based Fast Multi-Type Tree Decision Scheme for Luminance.- Light Gradient Boosting Machine Configurable Fast Block Partitioning for Luminance.- Learning-Based Fast Decision for Intra-Frame Prediction Mode Selection for Luminance.- Fast Intra-Frame Prediction Transform for Luminance Using Decision Trees.- Heuristic Based Fast Block Partitioning Scheme for Chrominance.- Conclusions.

Read more less

Book SynopsisThis book constitutes the thoroughly refereed conference proceedings of the First International Workshop on Design and Architecture for Signal and Image Processing, DASIP 2022, held in Budaypest, Hungary in June 2022. The 13 full included in the volume were carefully reviewed and selected from 32 submissions. They are organized in the following topical sections: leading signal, image and video processing and machine learning in custom embedded, edge and cloud computing architectures and systems.Table of ContentsSoftware and Architecture for Telecommunication Systems.- Towards Lightweight Deep-Learning Techniques.- Design Automation and Optimization Techniques for Embedded Hardware and Software.- Optimized Hardware and Software Implementations for Image Processing and Health Applications.

Read more less

Book SynopsisThe textbook presents basic concepts of signals and systems in a clear manner, based on the author’s 15+ years of teaching the undergraduate course for engineering students. To attain full benefit from the content, readers should have a strong knowledge of calculus and be familiar with integration, differentiation, and summation operations. The book starts with an introduction to signals and systems and continues with coverage of basic signal functions and their manipulations; energy, power, convolution, and systems; Fourier analysis of continuous time signals and digital signals; Laplace transform; and Z transforms. Practical applications are included throughout. The book is also packed with solved examples, self-study exercises, and end of chapter problems.Table of Contents1) Introduction to Signals and Systems2) BASIC SIGNAL FUNCTIONS and THEIR MANIPULATIONS3) ENERGY, POWER, CONVOLUTION, and SYSTEMS4) FOURIER ANALYSIS of DIGITAL SIGNALS5) FOURIER ANALYSIS of DIGITAL SIGNALS6) LAPLACE TRANSFORM7) Z Transform8) PRACTICAL APPLICATIONS

Read more less

Book SynopsisThis book presents the design, analysis, and application of nonlinear adaptive filters with the goal of improving efficient performance (ie the convergence speed, steady-state error, and computational complexity). The authors present a nonlinear adaptive filter, which is an important part of nonlinear system and digital signal processing and can be applied to diverse fields such as communications, control power system, radar sonar, etc. The authors also present an efficient nonlinear filter model and robust adaptive filtering algorithm based on the local cost function of optimal criterion to overcome non-Gaussian noise interference. The authors show how these achievements provide new theories and methods for robust adaptive filtering of nonlinear and non-Gaussian systems. The book is written for the scientist and engineer who are not necessarily an expert in the specific nonlinear filtering field but who want to learn about the current research and application. The book is also written to accompany a graduate/PhD course in the area of nonlinear system and adaptive signal processing.Table of Contents1) ​Adaptive filter2) Volterra adaptive filter3) FLANN adaptive filter4) Spline adaptive filter5) Kernel adaptive filters

Read more less

Book SynopsisThis book covers the theory of multidimensional signals and systems and related practical aspects. It extends the properties and mathematical tools of one-dimensional signals and systems to multiple dimensions and covers relevant timeless topics including multidimensional transformations, multidimensional sampling as well as discrete multidimensional systems. A special emphasis is placed on physical systems described by partial differential equations, the construction of suitable integral transformations and the implementation of the corresponding discrete-time algorithms. To this end, signal spaces and functional transformations are introduced at a mathematical level provided by undergraduate programs in engineering and science.The presentation takes a comprehensive, illustrative and educational approach without reference to a particular application field. Instead, the book builds a solid theoretical concept of multidimensional signals and systems and shows the application to various problems relevant for practical scenarios.Table of Contents

Read more less

Book SynopsisThis book constitutes the thoroughly refereed conference proceedings of the 16th International Workshop on Design and Architecture for Signal and Image Processing, DASIP 2023, held in Toulouse, France in January 2023.The 9 full included in the volume were carefully reviewed and selected from 17 submissions. They are organized in the following topical sections: Methods and Applications, Hardware Architectures and Implementations and others. Table of ContentsMethods and Applications.- SCAPE: HW-Aware Clustering of Data ow Actors for Tunable Scheduling Complexity.-Deep Recurrent Neural Network performing spectral recurrence on hyperspectral images for brain tissue classi cation.- Brain blood vessel segmentation in hyperspectral images through linear operators.- Neural Network Predictor for Fast Channel Change on DVB Set-Top-Boxes.- Hardware Architectures and Implementations.- AINoC: new interconnect for future Deep Neural Network accelerators.- Real-time FPGA implementation of the Semi-Global Matching stereo vision algorithm for an 4K/UHD video stream.- TaPaFuzz - An FPGA-Accelerated Framework for RISC-V IoT Graybox Fuzzing Adaptive Inference for FPGA-based 5G Automatic Modulation.- Classfication.- High-Level Online Power Monitoring of FPGA IP Based on Machine Learning.

Read more less

Book SynopsisThis book investigates the image watermarking domain, analyzing and comparing image watermarking techniques that exist in current literature. The author’s goal is to aid researchers and students in their studies in the vast and important domain of image watermarking, including its advantages and risks. The book has three chapters: image watermarking using data compression; speech modulation for image watermarking; and secure image watermarking based on LWT and SVD.In addition, this book: Investigates the image watermarking domain, analyzing and comparing current image watermarking techniques Includes detail on image encryption and mathematical tools used for image watermarking Covers image watermarking using data compression, speech modulation for image watermarking, and more Table of ContentsIntroduction.- Image watermarking using data compression.- Speech modulation for image watermarking.- Secure Image Watermarking Based on LWT and SVD.- Speech Signal Embedding into Digital Images Using Encryption and Watermarking Techniques.- Conclusion.

Read more less

Book Synopsis

Read more less

Book Synopsis

Read more less

Book SynopsisFundamentals of Inertial Navigation, Satellite-based Positioning and their Integration is an introduction to the field of Integrated Navigation Systems. It serves as an excellent reference for working engineers as well as textbook for beginners and students new to the area. The book is easy to read and understand with minimum background knowledge. The authors explain the derivations in great detail. The intermediate steps are thoroughly explained so that a beginner can easily follow the material. The book shows a step-by-step implementation of navigation algorithms and provides all the necessary details. It provides detailed illustrations for an easy comprehension. The book also demonstrates real field experiments and in-vehicle road test results with professional discussions and analysis. This work is unique in discussing the different INS/GPS integration schemes in an easy to understand and straightforward way. Those schemes include loosely vs tightly coupled, open loop vs closed loop, and many more. Table of ContentsReference Frames and Earth Geometry.- Global Positioning System.- Inertial Navigation System.- Inertial Navigation System Modeling.- Modeling INS Errors by Linear State Equations.- Kalman Filter.- INS/GPS integration.- Three Dimensional Reduced Inertial Sensor System / GPS Integration for Land-Based Vehicles.- Two Case Studies- full IMU/GPS and 3D RISS/GPS Integration.

Read more less

Book SynopsisField-Programmable Gate Arrays (FPGAs) are revolutionizing digital signal processing. The efficient implementation of front-end digital signal processing algorithms is the main goal of this book. It starts with an overview of today's FPGA technology, devices and tools for designing state-of-the-art DSP systems. A case study in the first chapter is the basis for more than 40 design examples throughout. The following chapters deal with computer arithmetic concepts, theory and the implementation of FIR and IIR filters, multirate digital signal processing systems, DFT and FFT algorithms, advanced algorithms with high future potential, and adaptive filters. Each chapter contains exercises. The VERILOG source code and a glossary are given in the appendices. This new edition incorporates Over 10 new system level case studies designed in VHDL and Verilog A new chapter on image and video processing An Altera Quartus update and new Model Sim simulations Xilinx Atlys board and ISIM simulation support Signed fixed point and floating point IEEE library examples An overview on parallel all-pass IIR filter design ICA and PCA system level designs Speech and audio coding for MP3 and ADPCM Table of ContentsComputer Arithmetic.- Finite Impulse Response (FIR) Digital Filtres.- Infinite Impulse Response (IIR) Digital Filtres.- Multirate Signal Processing.- Fourier Transforms.- Advanced Topics.- Adaptive Filtres.- Microprocessor Design.

Read more less

Book SynopsisIn der hochbitratigen optischen Nachrichtentechnik ist es wichtig, parasitäre induktive und kapazitive Einflüsse auf die Funktion von Laser- und Fotodioden zu kompensieren. Wegen des nichtlinearen Charakters der u-i-Relationen der Induktivitäten, Kapazitäten und Widerstände ist es möglich, Kompensationsverfahren gegen parasitäre Effekte zu entwickeln oder die Nichtlinearitäten gezielt zur Signalübertragung einzusetzen. Reiner Thiele beweist, dass bei Applikation der vorgestellten Kompensationsverfahren kapazitive und induktive Influenzen auf die Grundfunktion der optoelektronischen Bauelemente vermeidbar sind, das Klemmenverhalten durch die u-i-Kennlinien von Laser- oder Fotodioden komplett erfasst wird und ungünstige Einflüsse der Systemumgebung auf die optoelektronischen Schaltungen vermieden werden. Außerdem stellt er Definitionen für optoelektronische Grundstromkreise sowie ihre Berechnung für die Applikation gleichartiger Laser- oder Fotodioden als Sende- bzw. Empfangsbauelemente der optischen Nachrichtentechnik vor.Der Autor: Prof. Dr.-Ing. Reiner Thiele lehrte an der Hochschule Zittau/Görlitz und unterrichtet derzeit an der Staatlichen Studienakademie Bautzen.Table of ContentsParameter von Dioden.- Kompensation elektromagnetischer Beeinflussungen.- Optoelektronische Grundstromkreise.

Read more less

Book SynopsisThis book presents the peer-reviewed proceedings of the Sixth International Conference on Intelligent Computing and Applications (ICICA 2020), held at Government College of Engineering, Keonjhar, Odisha, India, during December 22–24, 2020. The book includes the latest research on advanced computational methodologies such as neural networks, fuzzy systems, evolutionary algorithms, hybrid intelligent systems, uncertain reasoning techniques, and other machine learning methods and their applications to decision-making and problem-solving in mobile and wireless communication networks.Table of ContentsClosed Loop Vision Based Ball Balancer.- A Novel Network Learning For Image Compressive Sensing.- COVID – 19 Severıty Predıctıons: An Analysis Usıng Correlatıon Measures.- A Novel Methodology for Comparative Analysis of Power Quality Improvement for a 3 Phase DC/AC Embedded DC/DC Converter.- Performance of Photovoltaic based ZETA Converter Water Pumping Application.- Performance Analysis of Radial Distribution System by Optimal Deployment of DG and DSTATCOM Considering Network Reconfiguration using a SAR Algorithm.

Read more less

Book SynopsisThis book provides insights into the Third International Conference on Intelligent Systems and Signal Processing (eISSP 2020) held By Electronics & Communication Engineering Department of G H Patel College of Engineering & Technology, Gujarat, India, during 28–30 December 2020. The book comprises contributions by the research scholars and academicians covering the topics in signal processing and communication engineering, applied electronics and emerging technologies, Internet of Things (IoT), robotics, machine learning, deep learning and artificial intelligence. The main emphasis of the book is on dissemination of information, experience and research results on the current topics of interest through in-depth discussions and contribution of researchers from all over world. The book is useful for research community, academicians, industrialists and postgraduate students across the globe.Table of ContentsChapter 1: Design and Analysis of Modified Split Ring Resonator Structured Multiband Antenna for WCDMA and WiMAX Applications.- Chapter 2: A Wearable Finger Exoskeleton For Motor Rehabilitation Using Mobile Application.- Chapter 3: Game theoretical approach for cluster-based routing protocol in Wireless Sensor Networks.- Chapter 4: Advance Digital Signal Processing for Interference Mitigation in Very High Throughput Satellite.- Chapter 5: Low-Power Endoscopic Image Compression Algorithms Using Modified Golomb Codes.- Chapter 6: Image Steganography Using Ridgelet Transform and SVD.- Chapter 7: HWCMA and HW-LS-CMA blind learning method for intelligent antenna system.- Chapter 8: Performance evaluation of prediction algorithm based tracking methods in a recovery of a lost target using Wireless Sensor Network.- Chapter 9: An Efficient Convolutional Neural Network for Acute Pain Recognition using HRV Features.- Chapter 10: Design and development of LSTM–RNN model for the prediction of RR intervals in ECG signals.- Chapter 11: FHSS Signals Classification by Linear Discriminant in a Multi-Signal Environment.- Chapter 12: Non-invasive Thyroid detection using thermal Imaging technique.- Chapter 13: Non Orthogonal Multiple Access Techniques for Next Generation Wireless Networks: A Review.- Chapter 14: Triple band circular patch antenna using complimentary split ring resonators.- Chapter 15: Features Analysis of Electroencephalography (EEG) for Mindfulness Meditation Effect on Cancer Patient toward Stress Level.

Read more less

Book SynopsisThis book presents select proceedings of the International Conference on Futuristic Communication and Network Technologies (CFCNT 2020) conducted at Vellore Institute of Technology, Chennai. It covers various domains in communication engineering and networking technologies. This volume comprises of recent research in areas like optical communication, optical networks, optics and optical computing, emerging trends in photonics, MEMS and sensors, active and passive RF components and devices, antenna systems and applications, RF devices and antennas for microwave emerging technologies, wireless communication for future networks, signal and image processing, machine learning/AI for networks, internet of intelligent things, network security and blockchain technologies. This book will be useful for researchers, professionals, and engineers working in the core areas of electronics and communication. Table of ContentsDeep Learning Based Image Preprocessing Techniques for Crop Disease Identification.- Performance Evaluation and Comparison Analysis of AODV and RPL using NetSim in Low Power, Lossy Networks.- Three Notched Bands Modified Hexagonal Patch Monopole Antenna.- An Internet of Things (IoT) based approach for Realtime Kitchen Monitoring using NodeMCU 1.0.- IoT Based Smart Irrigation and Monitoring System in Smart Agriculture.- Stock Price Prediction Based on Deep Learning Using Long Short Term Memory.

Read more less

Book SynopsisThis book gathers selected high-quality research papers presented at the 2nd International Conference on Advanced Computing Applications (ICACA 2021), held virtually during 27––28 March 2021. The book is divided into four sections. These are communication and computing, signal processing and multimedia, computational intelligence and data analytics and decision computing. The topics covered are advanced communication technologies, IoT-based systems and applications, network security and reliability, virtualization technologies, compressed sensors and multimedia applications, signal image and video processing, machine learning, pattern recognitions, intelligent computing, big data analytics, analytics in bio-computing, AI-driven 6G mobile wireless networks and autonomous driving.Table of ContentsInternet of Things-based Animal Health Monitoring and Management.- Cryptanalysis of an Authentication and Key Management Scheme in Context of Generic Hierarchical IoT Network.- Personalized Smart Recommendation System for Industrial Internet of Things.- IoT Based Anti-Poaching Technology to Save Wildlife.- GeoLens: Geospatial Location Exploration Using Mobile Crowdsensing in Tourism 4.0: A case study of Kunjanagar, Falakata, West Bengal.- IoT Cloud System for Streetlights Monitoring based on Solar Energy using ESP32.- Smart Vehicle Management System using Internet of Vehicles (IoV).- IoT Based Real Time HRV Performance Analysis.- Implementation of Acoustic Source Localization on Edge-IoT Platform.- Internet of Things Platform for Advantageous Renewable Energy Generation.

Read more less

Book SynopsisThis book is a collection of the papers accepted by the ICIVIS 2021—The International Conference on Image, Vision and Intelligent Systems held on June 15–17, 2021, in Changsha, China. The topics focus but are not limited to image, vision and intelligent systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings.Table of ContentsImage and Vision.- Intelligent Systems.- Computation and Application.

Read more less

Book SynopsisThis book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. It also highlights the directions for further development in image forgery detection. The book includes various publicly available standard image copy-move forgery datasets that are experimentally analyzed and presented with complete descriptions. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques. The key focus of work is to reduce the computational time without adversely affecting the efficiency of these techniques. In addition, these techniques are also robust to geometric transformation attacks like rotation, scaling, or both.Table of ContentsIntroduction.- Background Study and Analysis.- Copy-Move Forgery Detection using Local Binary Pattern Histogram Fourier Features.- Blur Invariant Block-based CMFD System using FWHT Features.- Geometric Transformation Invariant Improved Block based Copy-Move Forgery Detection.- Key-points based Enhanced Copy-Move Forgery Detection System using DBSCAN Clustering Algorithm.- Image Copy-Move Forgery Detection using Deep Convolutional Neural Networks.

Read more less

Book SynopsisThe book is a collection of best selected research papers presented at the International Conference on Advances in Information Communication Technology and Computing (AICTC 2021), held in Government Engineering College Bikaner, Bikaner, India, during 20–21 December 2021. The book covers ICT-based approaches in the areas of ICT for energy efficiency, life cycle assessment of ICT, green IT, green information systems, environmental informatics, energy informatics, sustainable HCI or Artificial intelli computational sustainability.Table of ContentsChapter 1. Smart Society Development Analysis and Controlbased on an Inductive Inference Method.- Chapter 2. The Emergence of sustainability Adoption in the Healthcare Sector during Covid-19.- Chapter 3. Ultra Wide Band Radar System for Respiratory Detection and Localization of Static Multi-Targets in LOS confined Environment.- Chapter 4. Omnichannel Integration Quality, Perceived Value and Brand Loyalty in the consumer electronics market: The Mediating effect of Consumer Personality.- Chapter 5. Examining the Impact of Incorporating Big Data Analytics in Agriculture.- Chapter 6. Online Teaching Strategies for IT Education.- Chapter 7. Smart and Intelligent Health Monitoring System.- Chapter 8. Energy Efficient OLSR Routing Protocol for Flying Ad-Hoc Networks.- Chapter 9. Challenges in Malware Detection and effecting areas: Survey.- Chapter 10. Integrated Smart IoT Infrastructure Management using Window Blockc­­hain and Whale LSTM Approaches.- Chapter 11. Driving analysis for load and fuel consumption using OBD II diagnostics.- Chapter 12. 2D and 3D Human Pose Estimation and Analysis using Deep Learning.- Chapter 13. The Comprehensive Art of Atmospheric Turbulence Mitigation Methodologies for Visible and Infrared Sequences.- Chapter 14. Graphical interpretation and multi-dimensional data visualization on Heart Disease Dataset.

Read more less

Book SynopsisThis book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and healthcare, to supply chain management, image processing, and cryptanalysis. It gathers high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2021), organized online. The book offers valuable insights into soft computing for teachers and researchers alike; the book will inspire further research in this dynamic field.

Read more less

Book SynopsisThis book gathers selected papers presented at the conference “Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology,” one of the first initiatives devoted to the problems of 3D imaging in all contemporary scientific and application areas. The two volumes of the book cover wide area of the aspects of the contemporary multidimensional imaging and outline the related future trends from data acquisition to real-world applications based on new techniques and theoretical approaches. This volume contains papers devoted to the theoretical representation and analysis of the 3D images. The related topics included are 3D image transformation, 3D tensor image representation, 3D content generation technologies, 3D graphic information processing, VR content generation technologies, multi-dimensional image processing, dynamic and auxiliary 3D displays, VR/AR/MR device, VR camera technologies, 3D imaging technologies and applications, 3D computer vision, 3D video communications, 3D medical images processing and analysis, 3D remote sensing images and systems, deep learning for image restoration and recognition, neural networks for MD image processing, etc.Table of ContentsColor Restoration of RGB-NIR Images in Low-light Environment Using CycleGAN.- A Novel Space Division Rough Set Model for Feature Selection.- Development of Mobile Food Recognition System Based on Deep Convolutional Network.- Image-Based Physics Rendering for 3D Surface Reconstruction: A Survey.- Network Intrusion Detection Based on Apriori-Kmeans Algorithm.- Global Analysis of Discrete S-I-R Models and S-I-S Systems.- Overview of SAR Image Change Detection Based on Segmentation.- Water Environmental Quality Assessment and Effect Prediction Based on Artificial Neural Network.- Full-Focus Imaging Detection of Ship Ultrasonic Phased Array Based on Directivity Function.- Longitudinal Structure Analysis and Segmentation Algorithm of Dongba Document.- Image Recognition Methods Based on Deep Learning.- Insulator Detection Study Based on Improved Faster-RCNN.- Comparative Analysis of Automatic Poetry Generation Systems Based on Different Recurrent Neural Networks.- Grid False Data Intrusion Detection Method Based on Edge Computing and Federated Learning.- Research on the Simulation of Informationized Psychological Sand Table Based on 3D Scene.- Innovative Design of Traditional Arts and Crafts Based on 3D Digital Technology.- Citrus Positioning Method Based On Camera And Lidar Data Fusion.- Research on Graphic Design of Digital Media Art based on Computer Aided Algorithm.- Ore Detection Method Based on YOLOv4.

Read more less

Book SynopsisThis book is a collection of the high-quality research articles in the field of computer vision and robotics which are presented in International Conference on Computer Vision and Robotics (ICCVR 2022), organized by BBD University Lucknow India, during 21 – 22 May 2022. The book discusses applications of computer vision and robotics in the fields like medical science, defence and smart city planning. This book presents recent works from researchers, academicians, industry, and policy makers.Table of ContentsStory Telling: Learning to Visualize Sentences Through Generated Scenes.- A Novel Processing of Scalable Web Log Data using Map Reduce Framework.- A Review of Disease Detection of Pre and Post-Harvest Plant Diseases: Recent Developments and Future.- Comparative Study Based on Lung Cancer with Covid-19 Using Deep Learning and Machine Learning.- Low-cost Data Acquisition System for Electric Vehicles.- Machine Learning based Robotic-Assisted Upper Limb Rehabilitation Therapies: A Review.- Performance Analysis of Classic LEACH vs CC-LEACH.- Anomaly Detection in the Course Evaluation Process.- Self Attention Based Efficient U-Net for Crack Segmentation.- Lung Carcinoma Detection from CT Images Using Image Segmentation.- A Deep Learning Based Human Activity Recognition System for Monitoring the Elderly People.- Tweets Classification on the Base of Sentiments using Deep Learning.

Read more less

Book SynopsisThis book presents selected research papers on current developments in the fields of soft computing and signal processing from the Fifth International Conference on Soft Computing and Signal Processing (ICSCSP 2022). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.Table of ContentsChapter 1. Microservice Architecture Observability Tool Analysis.- Chapter 2. Decentralized payment architecture for e-commerce and utility transactions with Government verified identities.- Chapter 3. Detection of Phishing Website using Intelligent Machine Learning Classifiers.- Chapter 4. Bidirectional Gated Recurrent Unit (BiGRU) based Bitcoin Price Prediction by News Sentiment Analysis.- Chapter 5. How AI Algorithms are being used in Applications.- Chapter 6. A Framework for Identifying Theft Detection using Multiple-instance Learning.- Chapter 7. An Efficient Reversible Data Hiding Based on Prediction Error Expansion.- Chapter 8. Deriving Insights from COVID-19.- Chapter 9. Smoke Detection in Forest Using Deep Learning.- Chapter 10. Pneumothorax Segmentation using Feature Pyramid Network and MobileNet Encoder through Radiography Images.- Chapter 11. Visual Learning with Dynamic Recall.- Chapter 12. Machine learning for drug discovery using ag-glomerative hierarchical clustering.- Chapter 13. Automated Photomontage Generation with Neural Style Transfer.- Chapter 14. Machine Learning Model Development Using Computational Neurology.- Chapter 15. Graph Theory based user profile extraction and community detection in Linkedin- A study. etc.

Read more less

Book SynopsisThis book reviews the most powerful attack strategies and potential defense mechanisms, always approaching the interplay between the Fusion Center and the Byzantines from a game-theoretic perspective. For each of the settings considered, the equilibria of the game and the corresponding payoffs are derived, shedding new light on the achievable performance level and the impact that the presence of the Byzantines has on the accuracy of decisions made by the Fusion Center. Accordingly, the book offers a simple yet effective introduction to the emerging field of adversarial information fusion, providing a wealth of intuitive take-home lessons for practitioners interested in applying the most basic notions to the design of practical systems, while at the same time introducing researchers and other readers to the mathematical details behind the theory. Table of ContentsIntroduction.- Preliminaries.- Security attacks and defenses in distributed sensor networks.- A Heuristic defense: A soft isolation algorithm for adversarial decision fusion.- Optimum decision fusion in the presence of Byzantines.- Nearly optimum decision fusion via message passing.- Decision fusion of hidden-Markov observations with synchronized attacks.- Decision fusion with unbalanced priors.- Decision fusion game with incomplete knowledge in a Bayesian setup.- Conclusions.

Read more less

Book SynopsisOptimizing Energy Consumption in LoRa Sensor Networks with the Nano Power System Timer TPL5111 for Forest Monitoring.- A comparative study of predicting stroke based on artificial intelligence algorithms.- Polyp Segmentation based on Mamba-MLP Mixer and Transformer.- Design and Implementation of a Chaos Injector to Improve Resilience in MQTT Based IoT Systems.- Adaptive Sliding Mode Control for Unmanned Surface Vehicle Using RBF Neural Network.- MambaU-Lite: A Lightweight Model based on Mamba and Integrated Channel Spatial Attention for Skin Lesion Segmentation.

Read more less

Book SynopsisThe volume is a collection of best selected research papers presented at International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2022) held at BITS Pilani, K K Birla Goa Campus, Goa, India during 23 – 25 September 2022. It includes state-of-the art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book will be useful for academicians, research scholars, and industry persons.Table of ContentsScenario Based Neural Network Model for Integrated Lighting Schemes in Residential Buildings.- Electrical Muscle Stimulation Models Identification Based on Hammerstein Structure and Gravitational Search Algorithm.- Experimental analysis of “A novel swarm intelligence optimization approach: sparrow search algorithm”.- Solving FJSP using Multi-agent system with GA.- A Comparative Analysis on Optimal Power Allocation and Pairing of User in Downlink NOMA System.

Read more less

Book SynopsisThis book presents the select peer-reviewed proceedings of the 2nd International Conference on Emerging Electronics & Automation (E2A) 2022. The proceedings aim to provide the reader with a view of the latest scientific efforts and achievements of the participants in the emerging fields including instrumentation, control, signal processing, communication, and associated computational techniques. It covers diverse fields of electronics, computation, automation, microelectronic technology, nanomaterials, and biomedical engineering applications. This volume will be of interest to those in academia and industry.Table of ContentsA Computational Aspect to Analyse Impact of Nutritional Status on the Development of Cardiovascular Diseases.- Vernacular Language Handwriting Recognition using Deep Learning Techniques.- FPGA Implementation of Efficient Softmax Architecture for Deep Neural Networks.- Multi-stage and multi-objective dynamic optimization-based scheduling of uncertain hybrid renewable energy systems with real-time energy compensation.- Design of Regenerative Snubber Circuit for Motor Drivers.- Clustering based multi-objective stochastic optimization approach in scheduling optimal energy dispatch of multiple energy sources in the presence of uncertainty.- Unfalsified Adaptive Control of a Robotic System.- Semi-Active Control for Seismic Vibration Mitigation of Building System with Magnetorheological Damping Device.- Relative Ageing of Population and Subpopulations in Proportional Reversed Hazard Frailty Models.- Handwritten Word Recognition in English Language.- Digital Image Watermarking Using Integer Wavelet Transform and Singular Value Decomposition.- Effect of Shallow Learning Techniques and Feature Selection for Breast Cancer Detection.- Design and Development of a Optimized Fast Transformation Module (OpFTM) for GAN Accelerator with Computation Efficiency.- A Meta-heuristic Optimized-based Classification Intrusion Detection System for BoT-IoT.- Fusion Spectrogram for Sound Classification Using 2D Convolutional Neural Network.- Design and Implementation of Garbage Detection and Classification Using YOLO-V5.- Simulations towards design of Matching Layer in Acoustic Emission Sensor.- Virtual Impedance Based Advanced Droop Control for Improved Dynamic Power Sharing in Islanded Microgrid.- A Parallel Signal Detector Approach for Detection of Human Activities Using Multiple Seismic Sensors.- Study of Dielectric Characteristics of Forsterite Based Medical Implant.- Performance Evaluation and Assessment of 100kW Grid Tied SPV System in Subtropical Climatic Conditions.- Analysis and Experimental Validation of SPWM and SVPWM Techniques on Two-level Three-phase VSI.- Performance Analysis of Fuzzy Logic with P&O MPPT for Grid Connected Solar PV System under Varying Solar Irradiance.- Switched-Boost-Modified Z-Source Inverter for Renewable Energy Application.- Vibration Energy Harvester using piezoelectric with truncated cone rectangular beam structure for low power applications.

Read more less